Risk prediction of esophageal squamous-cell carcinoma with common genetic variants and lifestyle factors in Chinese population

被引:36
作者
Chang, Jiang [1 ,2 ]
Huang, Ying [1 ,2 ]
Wei, Lixuan [1 ,2 ]
Ma, Baoshan [3 ]
Miao, Xiaoping [4 ]
Li, Yun [5 ]
Hu, Zhibin
Yu, Dianke [1 ,2 ]
Jia, Weihua [6 ]
Liu, Yu [1 ,2 ]
Tan, Wen [1 ,2 ]
He, Zhonghu [7 ,8 ]
Ke, Yang [8 ]
Wu, Tangchun [4 ]
Shen, Hongbing [7 ]
Zeng, Yixin [6 ]
Wu, Chen [1 ,2 ]
Lin, Dongxin [1 ,2 ]
机构
[1] Chinese Acad Med Sci, Canc Inst & Hosp, State Key Lab Mol Oncol, Beijing 100021, Peoples R China
[2] Peking Union Med Coll, Beijing 100021, Peoples R China
[3] Dalian Maritime Univ, Coll Informat Sci & Technol, Dalian, Liaoning, Peoples R China
[4] Huazhong Univ Sci & Technol, Minist Educ, Sch Publ Hlth, Key Lab Environm & Hlth, Wuhan 430074, Hubei, Peoples R China
[5] Univ N Carolina, Dept Genet, Chapel Hill, NC USA
[6] Sun Yat Sen Univ, Ctr Canc, State Key Lab Oncol Southern China, Guangzhou 510275, Guangdong, Peoples R China
[7] Nanjing Med Univ, Dept Epidemiol & Biostat, Ctr Canc, Nanjing, Jiangsu, Peoples R China
[8] Peking Univ, Sch Oncol, Beijing Canc Hosp & Inst, Key Lab Carcinogenesis & Translat Res,Minist Educ, Beijing 100871, Peoples R China
关键词
GENOME-WIDE ASSOCIATION; SUSCEPTIBILITY LOCI; CANCER-RISK; ALCOHOL-DRINKING; POLYMORPHISMS; METAANALYSIS; BREAST; PLCE1;
D O I
10.1093/carcin/bgt106
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Genome-wide association studies have identified multiple genetic variants associated with risk of esophageal squamous-cell carcinoma (ESCC) in Chinese populations. We examined whether these genetic factors, along with non-genetic factors, can contribute to ESCC risk prediction. We examined 25 single nucleotide polymorphisms (SNPs) and 4 non-genetic factors (sex, age, smoking and drinking) associated with ESCC risk in 9805 cases and 10 493 controls from Chinese populations. Weighted genetic risk score (wGRS) was calculated and logistic regression was used to analyze the association between wGRS and ESCC risk. We calculated the area under the curve (AUC) using receiver operating characteristic curve analysis to measure the discrimination after adding genetic variants to the model with only non-genetic factors. Net reclassification improvement (NRI) was used to quantify the degree of correct reclassification using different models. wGRS of the combined 17 SNPs with significant marginal effect (G SNPs) increased similar to 4-fold ESCC risk (P 1.49 10(164)) and the associations were significant in both drinkers and non-drinkers. However, wGRS of the eight SNPs with significant effect in gene drinking interaction (GE SNPs) increased similar to 4-fold ESCC risk only in drinkers (P-interaction 8.76 10(41)). The AUC for a risk model with 4 non-genetic factors, 17 G SNPs, 8 GE SNPs and their interactions with drinking was 70.1%, with the significant improvement of 7.0% compared with the model with only non-genetic factors (P < 0.0001). Our results indicate that incorporating genetic variants, lifestyle factors and their interactions in ESCC risk models can be useful for identifying patients with ESCC.
引用
收藏
页码:1782 / 1786
页数:5
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